AUTOMATIC ORIENTATION ADJUSTMENT OF SPHERICAL PANORAMA DIGITAL IMAGES

    公开(公告)号:US20180061011A1

    公开(公告)日:2018-03-01

    申请号:US15251500

    申请日:2016-08-30

    CPC classification number: G06T5/002 G06T5/006 G06T7/0024 G06T7/30 H04N5/23238

    Abstract: The present disclosure includes methods and systems for correcting distortions in spherical panorama digital images. In particular, one or more embodiments of the disclosed systems and methods correct for tilt and/or roll in a digital camera utilized to capture a spherical panorama digital images by determining a corrected orientation and generating an enhanced spherical panorama digital image based on the corrected orientation. In particular, in one or more embodiments, the disclosed systems and methods identify line segments in a spherical panorama digital image, map the line segments to a three-dimensional space, generate great circles based on the identified line segments, and determine a corrected orientation based on the generated great circles.

    Enhancement of skin, including faces, in photographs

    公开(公告)号:US09672414B2

    公开(公告)日:2017-06-06

    申请号:US14938568

    申请日:2015-11-11

    Abstract: An image processing application performs improved face exposure correction on an input image. The image processing application receives an input image having a face and ascertains a median luminance associated with a face region corresponding to the face. The image processing application determines whether the median luminance is less than a threshold luminance. If the median luminance is less than the threshold luminance, the application computes weights based on a spatial distance parameter and a similarity parameter associated with the median chrominance of the face region. The image processing application then computes a corrected luminance using the weights and applies the corrected luminance to the input image. The image processing application can also perform improved face color correction by utilizing stylization-induced shifts in skin tone color to control how aggressively stylization is applied to an image.

    Generating a Compact Video Feature Representation in a Digital Medium Environment

    公开(公告)号:US20180173958A1

    公开(公告)日:2018-06-21

    申请号:US15384831

    申请日:2016-12-20

    Abstract: Techniques and systems are described to generate a compact video feature representation for sequences of frames in a video. In one example, values of features are extracted from each frame of a plurality of frames of a video using machine learning, e.g., through use of a convolutional neural network. A video feature representation is generated of temporal order dynamics of the video, e.g., through use of a recurrent neural network. For example, a maximum value is maintained of each feature of the plurality of features that has been reached for the plurality of frames in the video. A timestamp is also maintained as indicative of when the maximum value is reached for each feature of the plurality of features. The video feature representation is then output as a basis to determine similarity of the video with at least one other video based on the video feature representation.

    Automatically selecting example stylized images for image stylization operations based on semantic content
    14.
    发明授权
    Automatically selecting example stylized images for image stylization operations based on semantic content 有权
    自动选择基于语义内容的图像样式化操作的示例风格化图像

    公开(公告)号:US09594977B2

    公开(公告)日:2017-03-14

    申请号:US14735822

    申请日:2015-06-10

    CPC classification number: G06T7/60 G06K9/00624 G06T7/90 G06T11/001

    Abstract: Systems and methods are provided for content-based selection of style examples used in image stylization operations. For example, training images can be used to identify example stylized images that will generate high-quality stylized images when stylizing input images having certain types of semantic content. In one example, a processing device determines which example stylized images are more suitable for use with certain types of semantic content represented by training images. In response to receiving or otherwise accessing an input image, the processing device analyzes the semantic content of the input image, matches the input image to at least one training image with similar semantic content, and selects at least one example stylized image that has been previously matched to one or more training images having that type of semantic content. The processing device modifies color or contrast information for the input image using the selected example stylized image.

    Abstract translation: 提供了系统和方法用于基于内容的图像样式化操作中使用的样式示例的选择。 例如,训练图像可用于识别示例风格化图像,其将在对具有某些类型的语义内容的输入图像进行风格化时生成高质量的程式化图像。 在一个示例中,处理设备确定哪个示例风格化图像更适合于使用由训练图像表示的某些类型的语义内容。 响应于接收或以其他方式访问输入图像,处理设备分析输入图像的语义内容,将输入图像与具有相似语义内容的至少一个训练图像匹配,并且选择至少一个先前已经具有的示例风格化图像 与具有该类型的语义内容的一个或多个训练图像匹配。 处理装置使用所选择的示例风格化图像修改输入图像的颜色或对比度信息。

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